Currently it seems like the algorithm to recommend/decide price changes dominantly triggers for dates where a change in occupancy is detected.
Market shifts and pricing changes in the compset are less often reflected in pricing decisions, it seems. This can easily lead to pricing oneself out of the market.
Maybe this is a problem that small hotels are more seeing because a nominally small change in occupancy (eg. 3-4 rooms being booked for a date) are relatively large changes in occupancy (like 10-20% maybe), which probably is a strong signal for atomize to raise prices, but when at the same time market remains unchanged or even moves lower, one is easily outpriced.
The other way round, if market changes (especially in the long booking window) happen, but no OTB changes are seen by atomize, it will not or only with a long delay adjust prices to meet market competitiveness again.

So I suggest that the algorithm should offer a tuning setting to allow to reduce weight on OTB changes and increase market datas influence.

Also the algorithm should take market data more into consideration for long booking windows (like 60-120 days) even if there is no or little pickup and adjust down/up more reliably.

So in summary I am asking for more transparent settings and weights, and allowing the algorithm to be adjusted to the hotel size and the relative impacts of OTB and market changes on the pricing decisions.